Datos

ipsa_sa

method Valor-p statistic parameter alternative resultado 95%
Augmented Dickey-Fuller Test 0.2727477 -2.720626 6 stationary Existe unit-root

Ajuste sigma logLik AIC BIC Box-Ljung test residuos p value
ARMA(6, 3) 0.1253277 162.0968 -302.1937 -263.8609 0.9973860
ARMA(4, 6) 0.1266724 159.0179 -294.0359 -252.2183 0.9902530
ARMA(5, 1) 0.1295415 153.7232 -291.4464 -263.5680 0.9880742
ARMA(5, 2) 0.1251125 161.5737 -305.1474 -273.7842 0.9871039
ARMA(2, 1) 0.1288197 153.5389 -297.0778 -279.6538 0.9855968
ARMA(5, 5) 0.1267081 159.0955 -294.1910 -252.3735 0.9851692
ARMA(5, 3) 0.1300808 153.7547 -287.5095 -252.6615 0.9846781
ARMA(6, 1) 0.1295148 154.2744 -290.5489 -259.1857 0.9838289
ARMA(2, 2) 0.1290851 153.5531 -295.1061 -274.1974 0.9816079
ARMA(4, 1) 0.1292969 153.6664 -293.3328 -268.9392 0.9811503
ARMA(1, 3) 0.1290591 153.6018 -295.2036 -274.2948 0.9774766
ARMA(4, 3) 0.1243410 161.5467 -305.0933 -273.7302 0.9771072

El modelo seleccionado es el Modelo ARMA(6, 3), el cual posee AIC de -302.193665. Los parámetros estimados son:

term estimate std.error 2.5 % 97.5 %
ar1 1.0047231 0.0772829 0.8532513 1.1561948
ar2 0.5282915 0.1140917 0.3046760 0.7519071
ar3 -1.1948315 0.1093457 -1.4091452 -0.9805179
ar4 0.2751198 0.0965644 0.0858572 0.4643825
ar5 0.1402198 0.0935722 -0.0431784 0.3236180
ar6 0.1160064 0.0672156 -0.0157337 0.2477464
ma1 -0.6109318 0.0520313 -0.7129113 -0.5089523
ma2 -0.6038494 0.0632301 -0.7277781 -0.4799208
ma3 0.9587595 0.0659419 0.8295157 1.0880033
intercept 0.2445498 0.0435035 0.1592845 0.3298150

Los residuos presentan los siguientes ACF, PACF:

ipsa_sa